Memory effects in stock price dynamics: evidences of technical trading

TL;DR

This paper investigates whether technical trading strategies, specifically supports and resistances, induce detectable memory effects in stock prices, providing evidence of self-reinforcing behaviors in financial markets.

Contribution

It introduces a new criterion to identify supports and resistances and demonstrates their association with memory effects in stock price dynamics.

Findings

Prices tend to bounce off supports and resistances more often than cross them.

Memory effects are linked to these key price levels, indicating self-fulfilling prophecies.

Technical trading influences price dynamics beyond random fluctuations.

Abstract

Technical trading represents a class of investment strategies for Financial Markets based on the analysis of trends and recurrent patterns of price time series. According standard economical theories these strategies should not be used because they cannot be profitable. On the contrary it is well-known that technical traders exist and operate on different time scales. In this paper we investigate if technical trading produces detectable signals in price time series and if some kind of memory effect is introduced in the price dynamics. In particular we focus on a specific figure called supports and resistances. We first develop a criterion to detect the potential values of supports and resistances. As a second step, we show that memory effects in the price dynamics are associated to these selected values. In fact we show that prices more likely re-bounce than cross these values. Such an effect is a quantitative evidence of the so-called self-fulfilling prophecy that is the self-reinforcement of agents' belief and sentiment about future stock prices' behavior.